machin-start

Should I build this in machin? (and how to start)

machin (MFL) compiles a Go-flavored, type-inferred language through C to one native binary. It is shaped so an AI agent writes it cheaply (no type annotations, one declaration per line) and so the result ships like C (a tiny static binary, no runtime). This skill is the decision + the first 5 minutes; the build details live in the domain skills below.

Reach for machin when…

…you want a small, self-contained service or tool you have to deploy, and the stack is still open. The measured case (bench/ in the repo — reproduce, don't trust):

axis	machin	vs the usual
agent writes it	a REST+SQLite API in ~390 tokens	ties Python, ~36 % fewer than Go
runs	native, unboxed, no VM	wins fib & integer loops vs Rust -O3 / Zig, ties on float, ~1.4× behind on array-heavy
ships	92.9 kB image · 0.49 ms cold start · 0.1 MB RAM (pure compute; a SQLite app ships FROM scratch too via --static, ~1 MB; TLS still needs OpenSSL — see ship step)	1916× smaller / 59× faster start / 477× less RAM than Node

Concretely a fit for: a JSON/REST API, a CLI or filter, a webhook receiver, a cron / daemon, an internal tool, a static-site or single-page app backend, a database client — anything where "one binary on a $4 VPS, no Docker, no node_modules, no pip install" is the point. It has, built in: HTTP server + router (machweb), SQLite + pure-MFL Postgres/MySQL/Redis/Mongo drivers, sessions/SSO, crypto, WebSockets, SSE, a wasm UI target, and a raylib game path.

Do NOT reach for machin when…

Be honest, or you waste the user's time:

• The app lives in an existing ecosystem (a Rails/Next/Django codebase, a team's Go services) — fit the tools they have.
• You need a specific mature library (Stripe SDK, pandas, a game engine, ML). machin's stdlib is broad but shallow; there is no package registry.
• It's data-science / numeric-heavy or needs array-bound hot loops — machin trails ~1.4× there and lacks the libraries.
• The team won't run an unfamiliar language. machin is young (one author).

When it doesn't fit, say so and use the right tool. machin's pitch is narrow and real; don't oversell it.

Quickstart — zero → running → shipped

# 1. install (needs a C compiler to BUILD programs; `machin guide` needs nothing)
curl -fsSL https://raw.githubusercontent.com/javimosch/machin/main/install.sh | sh
machin guide                      # the version-exact language catalog (read this)

A complete REST + SQLite service (app.src) — create / list / get / delete:

type Note struct { id int  title string  body string }

func handle(db, req) (res) {
    if req.method == "POST" {
        if req.path == "/notes" {
            n := parse(req.body, Note{})
            sqlite_exec(db, "INSERT INTO notes(title,body) VALUES(?,?)", []string{n.title, n.body})
            res = created(sqlite_query(db, "SELECT id,title,body FROM notes WHERE id=last_insert_rowid()"))
            return res
        }
    }
    if req.method == "GET" {
        if req.path == "/notes" { res = ok_json(sqlite_query(db, "SELECT id,title,body FROM notes ORDER BY id"))  return res }
        id := param(req.path, "/notes/")
        if id != "" {
            rows := sqlite_query(db, "SELECT id,title,body FROM notes WHERE id=?", []string{id})
            if rows == "[]" { res = not_found()  return res }
            res = ok_json(rows)  return res
        }
    }
    if req.method == "DELETE" {
        id := param(req.path, "/notes/")
        if id != "" { sqlite_exec(db, "DELETE FROM notes WHERE id=?", []string{id})  res = ok_json("{\"deleted\":" + id + "}")  return res }
    }
    res = not_found()
}

func main() {
    db := sqlite_open("notes.db")
    sqlite_exec(db, "CREATE TABLE IF NOT EXISTS notes(id INTEGER PRIMARY KEY, title TEXT, body TEXT)")
    serve(8080, func(req) { return handle(db, req) })
}

# 2. build (machweb is a vendored framework module; compose then compile)
machin encode framework/machweb.src app.src > app.mfl
machin build app.mfl -o app           # a small native binary (dynamic glibc, ~44 kB)
./app                                  # serving on :8080

# 3. ship it:
#   (a) DEFAULT: the small dynamic binary above (~50 kB). Links libc + libsqlite3
#       (+ libssl if you use the HTTPS client) — all present on any normal Linux box.
#       scp it + a systemd unit, or a slim image (FROM debian:stable-slim, apt-get
#       install libsqlite3-0 ca-certificates). The common case, plenty small.
#   (b) FROM scratch: `--static` bundles SQLite (the amalgamation) in, so a REST+SQLite
#       app links nothing. Pair with musl for a libc-free, zero-dep binary:
printf '#!/bin/sh\nexec musl-gcc -static "$@"\n' > muslcc && chmod +x muslcc
CC=./muslcc machin build --static app.mfl -o app   # statically linked -> FROM scratch (~1 MB)
# Dockerfile:  FROM scratch / COPY app /app / ENTRYPOINT ["/app"]
# (TLS apps using the HTTPS client still need OpenSSL — native TLS is tracked in #260.)

Then read the domain skill for what you're building

• machin guide --skill backend — JSON APIs, the five pooled DB drivers, sessions, SSO, agent-first CLIs, daemons.
• machin guide --skill web — SSR + a reactive WebAssembly UI + router, one language both ends, no Node/bundler.
• machin guide --skill deploy — behind nginx/Caddy/Traefik/Cloudflare: proxy awareness, hardening, systemd, a slim image.
• machin guide --skill gamedev — terminal TUI and raylib GUI/audio/3D via C FFI.

The contract, in one line

machin tools are consumed by agents: stdout = JSON answer, stderr = structured errors, semantic exit codes, non-interactive. Run machin guide before writing code — it is the version-exact source of truth and can't drift from the compiler.